Update app.py

app.py

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 📧 **Abstact**
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 Text-to-image diffusion models (T2I) use a latent representation of a text prompt to guide the image generation process. 
 However, the process by which the encoder produces the text representation is unknown. 
 We propose the Diffusion Lens, a method for analyzing the text encoder of T2I models by generating images from its intermediate representations. 
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 Exploring knowledge retrieval, we find that representation of uncommon concepts requires further computation compared to common concepts, 
 and that knowledge retrieval is gradual across layers. 
 Overall, our findings provide valuable insights into the text encoder component in T2I pipelines.
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 📧 **Contact**
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 If you have any questions, please feel free to open an issue or directly reach us out at <b>tok@cs.technion.ac.il
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 </b>.
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